Welcome to masskit_ai’s documentation!

Contents:

• Masskit_ai use and architecture
  • Setup for training peptide prediction models
    • Running training
      • Running training on a local linux machine
      • Output models
    • Creating predictions
      • Creating predictions on a local linux machine
  • Configuration
  • Using checkpoints and transfer learning
    • Checkpoints
    • Transfer learning
    • Bayesian networks
  • Creating models, losses, and new inputs or outputs to models
    • Software architecture
    • Custom models
    • Adding fields to the model input
    • Adding fields to the model output
    • Custom losses
    • Custom metrics
    • Custom sampler
  • Miscellaneous settings
• Recipes
  • Spectral library generation
    • Peptide library to spectral library
      • Example set of commands to predict spectra from a fasta file uniprot.fasta
  • Predicting RI values using AIRI
    • Example set of commands to calculate AIRI values from a CSV file my_csv.csv with SMILES in the molecules column
    • Example set of commands to calculate AIRI values from an SDF molfile my_sdf.sdf

Indices and tables

• Index

• Module Index

• Search Page